8,048 research outputs found
Easier Debugging of Multithreaded Software
Software activation is a technique designed to avoid illegal use of a licensed software. This is achieved by having a legitimate user enter a software activation key to validate the purchase of the software. Generally, a software is a single-threaded program. From an attacker’s perspective, who does not wish to pay for this software, it is not hard to reverse engineer such a single threaded program and trace its path of execution. With tools such as OllyDbg, the attacker can look into the disassembled code of this software and find out where the verification logic is being performed and then patch it to skip the verification altogether. In order to make the attacker’s task difficult, a multi-threaded approach towards software development was proposed [1]. According to this approach, you should break the verification logic into several pieces, each of which should run in a separate thread. Any debugger, such as OllyDbg, is capable of single-stepping through only one thread at a time, although it is aware of the existence of other threads. This makes it difficult for an attacker to trace the verification logic. Not just for an attacker, it is also difficult for any ethical developer to debug a multithreaded program. The motivation behind this project is to develop the prototype of a debugger that will make it easer to trace the execution path of a multi-threaded program. The intended debugger has to be able to single-step through all of the threads in lockstep
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Software integration testing based on communication coverage criteria and partial model generation
This paper considers the problem of integration testing the components of a timed distributed software system. We assume that communication between the components is specified using timed interface automata and use computational tree logic (CTL) to define communication-based coverage criteria that refer to send- and receive-statements and communication paths. The proposed method enables testers to focus during component integration on such parts of the specification, e.g. behaviour specifications or Markovian usage models, that are involved in the communication between components to be integrated. A more specific application area of this approach is the integration of test-models, e.g. a transmission gear can be tested based on separated models for the driver behaviour, the engine condition, and the mechanical and hydraulical transmission states. Given such a state-based specification of a distributed system and a concrete coverage goal, a model checker is used in order to determine the coverage or generate test sequences that achieve the goal. Given the generated test sequences we derive a partial test-model of the components from which the test sequences are derived. The partial model can be used to drive further testing and can also be used as the basis for producing additional partial models in incremental integration testing. While the process of deriving the test sequences could suffer from a combinatorial explosion, the effort required to generate the partial model is polynomial in the number of test sequences and their length. Thus, where it is not feasible to produce test sequences that achieve a given type of coverage it is still possible to produce a partial model on the basis of test sequences generated to achieve some other criterion. As a result, the process of generating a partial model has the potential to scale to large industrial software systems. While a particular model checker, UPPAAL, was used, it should be relatively straightforward to adapt the approach for use with other CTL based model checkers. A potential additional benefit of the approach is that it provides a visual description of the state-based testing of distributed systems, which may be beneficial in other contexts such as education and comprehension
SmartTrack: Efficient Predictive Race Detection
Widely used data race detectors, including the state-of-the-art FastTrack
algorithm, incur performance costs that are acceptable for regular in-house
testing, but miss races detectable from the analyzed execution. Predictive
analyses detect more data races in an analyzed execution than FastTrack
detects, but at significantly higher performance cost.
This paper presents SmartTrack, an algorithm that optimizes predictive race
detection analyses, including two analyses from prior work and a new analysis
introduced in this paper. SmartTrack's algorithm incorporates two main
optimizations: (1) epoch and ownership optimizations from prior work, applied
to predictive analysis for the first time; and (2) novel conflicting critical
section optimizations introduced by this paper. Our evaluation shows that
SmartTrack achieves performance competitive with FastTrack-a qualitative
improvement in the state of the art for data race detection.Comment: Extended arXiv version of PLDI 2020 paper (adds Appendices A-E) #228
SmartTrack: Efficient Predictive Race Detectio
An implementation of feasible path constraints generation for reproducible testing.
Non-determinism features make the testing of a concurrent program not repeatable. Specification-based reproducible testing is a promising technique that may give the tester more control over the environment of concurrent testing. With a given test case, the crucial part of the test scenario which contributes to achieving the control on the execution path are input events and path constraints in terms of synchronization events. The problem considered in this thesis is to generate a significant set of path constraints automatically from the design specification in terms of design abstract under the assumption that monitors are the key mechanism to handle the synchronization events. In addition, as a considerable feature, formal methods have been applied in the implementation tool to construct the path constraints.Dept. of Computer Science. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2004 .L55. Source: Masters Abstracts International, Volume: 43-01, page: 0239. Adviser: Jessica Chen. Thesis (M.Sc.)--University of Windsor (Canada), 2004
OSCAR. A Noise Injection Framework for Testing Concurrent Software
“Moore’s Law” is a well-known observable phenomenon in computer science that describes a
visible yearly pattern in processor’s die increase. Even though it has held true for the last 57
years, thermal limitations on how much a processor’s core frequencies can be increased, have
led to physical limitations to their performance scaling. The industry has since then shifted
towards multicore architectures, which offer much better and scalable performance, while in
turn forcing programmers to adopt the concurrent programming paradigm when designing new
software, if they wish to make use of this added performance. The use of this paradigm comes
with the unfortunate downside of the sudden appearance of a plethora of additional errors in
their programs, stemming directly from their (poor) use of concurrency techniques.
Furthermore, these concurrent programs themselves are notoriously hard to design and to
verify their correctness, with researchers continuously developing new, more effective and effi-
cient methods of doing so. Noise injection, the theme of this dissertation, is one such method. It
relies on the “probe effect” — the observable shift in the behaviour of concurrent programs upon
the introduction of noise into their routines. The abandonment of ConTest, a popular proprietary
and closed-source noise injection framework, for testing concurrent software written using the
Java programming language, has left a void in the availability of noise injection frameworks for
this programming language.
To mitigate this void, this dissertation proposes OSCAR — a novel open-source noise injection
framework for the Java programming language, relying on static bytecode instrumentation for
injecting noise. OSCAR will provide a free and well-documented noise injection tool for research,
pedagogical and industry usage. Additionally, we propose a novel taxonomy for categorizing new
and existing noise injection heuristics, together with a new method for generating and analysing
concurrent software traces, based on string comparison metrics.
After noising programs from the IBM Concurrent Benchmark with different heuristics, we
observed that OSCAR is highly effective in increasing the coverage of the interleaving space, and
that the different heuristics provide diverse trade-offs on the cost and benefit (time/coverage) of
the noise injection process.Resumo
A “Lei de Moore” é um fenómeno, bem conhecido na área das ciências da computação, que
descreve um padrĂŁo evidente no aumento anual da densidade de transĂstores num processador.
Mesmo mantendo-se válido nos últimos 57 anos, o aumento do desempenho dos processadores
continua garrotado pelas limitações térmicas inerentes `a subida da sua frequência de funciona-
mento. Desde entĂŁo, a industria transitou para arquiteturas multi nĂşcleo, com significativamente
melhor e mais escalável desempenho, mas obrigando os programadores a adotar o paradigma
de programação concorrente ao desenhar os seus novos programas, para poderem aproveitar o
desempenho adicional que advém do seu uso. O uso deste paradigma, no entanto, traz consigo,
por consequência, a introdução de uma panóplia de novos erros nos programas, decorrentes
diretamente da utilização (inadequada) de técnicas de programação concorrente.
Adicionalmente, estes programas concorrentes sĂŁo conhecidos por serem consideravelmente
mais difĂceis de desenhar e de validar, quanto ao seu correto funcionamento, incentivando investi-
gadores ao desenvolvimento de novos métodos mais eficientes e eficazes de o fazerem. A injeção
de ruĂdo, o tema principal desta dissertação, Ă© um destes mĂ©todos. Esta baseia-se no “efeito sonda”
(do inglês “probe effect”) — caracterizado por uma mudança de comportamento observável em
programas concorrentes, ao terem ruĂdo introduzido nas suas rotinas. Com o abandono do Con-
Test, uma framework popular, proprietária e de código fechado, de análise dinâmica de programas
concorrentes atravĂ©s de injecção de ruĂdo, escritos com recurso `a linguagem de programação Java,
viu-se surgir um vazio na oferta de framework de injeção de ruĂdo, para esta mesma linguagem.
Para mitigar este vazio, esta dissertação propõe o OSCAR — uma nova framework de injeção de
ruĂdo, de cĂłdigo-aberto, para a linguagem de programação Java, que utiliza manipulação estática
de bytecode para realizar a introdução de ruĂdo. O OSCAR pretende oferecer uma ferramenta
livre e bem documentada de injeção de ruĂdo para fins de investigação, pedagĂłgicos ou atĂ© para
a indústria. Adicionalmente, a dissertação propõe uma nova taxonomia para categorizar os dife-
rentes tipos de heurĂsticas de injecção de ruĂdos novos e existentes, juntamente com um mĂ©todo
para gerar e analisar traces de programas concorrentes, com base em métricas de comparação de
strings.
ApĂłs inserir ruĂdo em programas do IBM Concurrent Benchmark, com diversas heurĂsticas, ob-
servámos que o OSCAR consegue aumentar significativamente a dimensĂŁo da cobertura do espaço de estados de programas concorrentes. Adicionalmente, verificou-se que diferentes heurĂsticas
produzem um leque variado de prós e contras, especialmente em termos de eficácia versus
eficiĂŞncia
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